If you surveyed 10 people, you’d get 10 different definitions for each and probably a lot of “umms”.

So let’s talk about road tripping instead.

Think of how our process for planning how to get from point A to point B has changed over time.

Atlas - Remember when you had to have an actual, physical, printed and purchased book in your vehicle? You found point B on the map and looking at all the roads that get there, find the seemingly best route from point A. Then hope you don’t miss a turn.

Mapquest - Then Mapquest helped us skip the process of building the best route. You went to the website, entered the destination and starting location, then print out directions.

Apple/Google Maps v. 1 - Then life got good. We opened up an app on our smartphones to see the best route. Sure sometimes you had take a few extra u-turns but it beat the alternative.

Apple/Google Maps today - The app tells us the fastest route, shortest route, which route takes us by our favorite stops and warns us mid-route if there’s an accident up ahead and a detour would be faster.

So here we are, living our best cartographical (?) lives.

We have the information we need at the tip of our fingers and real time recommendations we can use to decide whether to take the scenic route or the fastest route.

Excel gave us the ability to do extensive analysis of time series data.

Cloud computing gives us the ability to crunch a whole lot of numbers in a lot less time.

Machine learning and artificial intelligence applied in the right contexts unleash the power of predictive (what will likely happen?) and prescriptive analytics (what should I do about it?). If done right, these powerful tools allow the user to interact with the technology to get the best outcome.

While machine learning & artificial intelligence might seem intimidating to those currently & exclusively devoted to Excel, just think of it as putting down the Atlas, picking up your iPhone and opening Google Maps….for decision makers.